TY - JOUR
T1 - Distributed and Mixed Information in Monosynaptic Inputs to Dopamine Neurons
AU - Tian, Ju
AU - Huang, Ryan
AU - Cohen, Jeremiah Y.
AU - Osakada, Fumitaka
AU - Kobak, Dmitry
AU - Machens, Christian K.
AU - Callaway, Edward M.
AU - Uchida, Naoshige
AU - Watabe-Uchida, Mitsuko
N1 - Funding Information:
We thank N. Eshel for comments, C. Dulac for sharing resources, V. Rao for technical assistance, M. Shoji for training assistance, and M. Nagashima for histology assistance. This work was supported by the Dr. Mortier and Theresa Sackler Foundation (to J.T.), National Institute of Mental Health Grants R01MH095953 and R01MH101207 (to N.U.), NIH Grant MH063912 (to E.M.C.), the Japan Society for the Promotion of Science and Japan Science and Technology Agency (to F.O.), and Bial Foundation Grant 389/14 (to D.K.).
Publisher Copyright:
© 2016 Elsevier Inc.
PY - 2016/9/21
Y1 - 2016/9/21
N2 - Dopamine neurons encode the difference between actual and predicted reward, or reward prediction error (RPE). Although many models have been proposed to account for this computation, it has been difficult to test these models experimentally. Here we established an awake electrophysiological recording system, combined with rabies virus and optogenetic cell-type identification, to characterize the firing patterns of monosynaptic inputs to dopamine neurons while mice performed classical conditioning tasks. We found that each variable required to compute RPE, including actual and predicted reward, was distributed in input neurons in multiple brain areas. Further, many input neurons across brain areas signaled combinations of these variables. These results demonstrate that even simple arithmetic computations such as RPE are not localized in specific brain areas but, rather, distributed across multiple nodes in a brain-wide network. Our systematic method to examine both activity and connectivity revealed unexpected redundancy for a simple computation in the brain.
AB - Dopamine neurons encode the difference between actual and predicted reward, or reward prediction error (RPE). Although many models have been proposed to account for this computation, it has been difficult to test these models experimentally. Here we established an awake electrophysiological recording system, combined with rabies virus and optogenetic cell-type identification, to characterize the firing patterns of monosynaptic inputs to dopamine neurons while mice performed classical conditioning tasks. We found that each variable required to compute RPE, including actual and predicted reward, was distributed in input neurons in multiple brain areas. Further, many input neurons across brain areas signaled combinations of these variables. These results demonstrate that even simple arithmetic computations such as RPE are not localized in specific brain areas but, rather, distributed across multiple nodes in a brain-wide network. Our systematic method to examine both activity and connectivity revealed unexpected redundancy for a simple computation in the brain.
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U2 - 10.1016/j.neuron.2016.08.018
DO - 10.1016/j.neuron.2016.08.018
M3 - Article
C2 - 27618675
AN - SCOPUS:84991227609
SN - 0896-6273
VL - 91
SP - 1374
EP - 1389
JO - Neuron
JF - Neuron
IS - 6
ER -